Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Code Analysis”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 991 records · Page 55
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Impact of hohlraum cooling on ignition metrics for inertial fusion implosions

This paper extends the evaluation of ignition metrics to include the impact of hohlraum cooling before peak implosion velocity in radiation driven implosions. First, we provide an extension of the results for the key hot spot stagnation quantities from the 2018 paper. The modified analytic expressions presented here match the Hydra results for these National Ignition Facility scale implosions both with and without hohlraum cooling before peak velocity if the effective ablation pressure P abl (effective) = P abl (t pv - 0.5 ns) is used in the analytic formulas, where t pv is the time of peak implosion velocity. Second, we provide an analysis that enables a comparison of the Hydra radiation hydrodynamics code calculations utilized here with the predictions of the analytic piston model of an ICF implosion, which focused on sensitivity to time duration of the hohlraum cooling phase before peak velocity (often called the “coast time”) and the shell radius at peak velocity R pv . Third, we provide a set of ignition metrics that are valid across a wide range of capsule designs valid for implosions both with and without hohlraum cooling before peak implosion velocity is reached.

42 ENGINEERING↗
DOE OSTI2022

Simple and statistically sound recommendations for analysing physical theories

Physical theories that depend on many parameters or are tested against data from many different experiments pose unique challenges to statistical inference. Many models in particle physics, astrophysics and cosmology fall into one or both of these categories. These issues are often sidestepped with statistically unsound ad hoc methods, involving intersection of parameter intervals estimated by multiple experiments, and random or grid sampling of model parameters. Whilst these methods are easy to apply, they exhibit pathologies even in low-dimensional parameter spaces, and quickly become problematic to use and interpret in higher dimensions. In this article we give clear guidance for going beyond these procedures, suggesting where possible simple methods for performing statistically sound inference, and recommendations of readily-available software tools and standards that can assist in doing so. Our aim is to provide any physicists lacking comprehensive statistical training with recommendations for reaching correct scientific conclusions, with only a modest increase in analysis burden. Furthermore, our examples can be reproduced with the code publicly available at Zenodo.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Convergence of halo statistics: code comparison between rockstar and compaso using scale-free simulations

ABSTRACT In this study, we perform a halo-finder code comparison between rockstar and compaso. Based on our previous analysis aiming at quantifying resolution of N-body simulations by exploiting large (up to N = 40963) simulations of scale-free cosmologies run using abacus, we focus on convergence of the halo mass function, two-point correlation function, and mean radial pairwise velocities of halo centres selected with the aforementioned two algorithms. We establish convergence, for both rockstar and compaso, of mass functions at the 1 per cent precision level and of the mean pairwise velocities (and also two-point correlation function) at the 2 per cent level. At small scales and masses, we find that rockstar exhibits greater self-similarity. We also highlight the role played by the merger-tree post-processing of compaso haloes on their convergence. Finally, we give resolution limits expressed as a minimum particle number per halo in a form that can be directly extrapolated to Lambda cold dark matter.

Astronomy & Astrophysics↗
DOE OSTI2020

ALLOY SELECTION AND C-276 CODE DESIGN VALUE EXTENSION FOR ADVANCED MOLTEN SALT TECHNOLOGY TEST FACILITIES EXPERIMENTATION

Molten halide salts are being considered as working fluids for nuclear and concentrated solar power applications. High temperature molten fluoride and chloride salts are known to preferentially attack and deplete Cr in alloys, which leads to the use of high-Ni lower-Cr alloys in test facilities for advanced Molten Salt Technology. Alloys 600 and C-276 are two commercially available Ni alloys that have moderate Cr contents and are qualified to the maximum temperature of 649°C and 677°C (1,200°F and 1,251°F), respectively, in the Boiler and Pressure Vessel Code. Both alloys have good corrosion resistance to acids, are resistant to stress-corrosion cracking, and have long track records of use in the chemical industry. Comparatively, Alloy C-276 has a similar Cr content but much higher allowable stresses for temperatures greater than 600°C (1,112°F). Therefore, it has been considered as a structural material for test facilities that require operations at 700°C (1,292°F) or greater to develop high-temperature Molten Salt Technology. To meet the requirements, the current code design values were extended based on some experimental data. Analysis showed that above current Codified maximum temperature, strength of the alloy is mainly controlled by creep rupture life under the average stress, although the Sc creep rate criterion is close to the Favg.Savg rupture criterion. This paper presents the intended test facilities and the design requirements, alloy selection considerations, literature review, data analysis, and proposed allowable stress extension based on some creep test data for C-276 at temperatures greater than 677°C (1,251°F). Further research activities are also briefly mentioned.

Ren, Weiju↗
DOE OSTI2021

A Discussion of Strength Reduction Factor Development for Thermal Aging Effect on Nuclear Structural Alloys

In consideration of structural alloy property deterioration during long-term exposure to elevated temperatures, the yield and ultimate tensile strength reduction factors are provided in the Boiler and Pressure Vessel Code Section III for nuclear reactor component design and operation analysis. Because the Gen IV reactor requirement of 40 ~ 60 years of service life makes it difficult to acquire such long exposure test data for developing the reduction factors, they must be derived from test data with relatively short exposure by predictive methods considered to be reasonably reliable. A novel approach with a physically-based model has recently been proposed for application to development of reduction factors for 9Cr-1Mo-V. In the model, contributors to the tensile strength are first identified and related to definite microstructural features of the alloy, then some physically-based methods are employed to simulate the microstructural evolution, and finally the model is assembled with test-data-calibrated parameters to generate the yield and ultimate tensile strength reduction factors covering elevated temperature exposure for up to 57 years. The approach is undoubtedly a trailblazing development that will, if proven reliable, lead to a paradigm shift in predicting thermal aging behavior of many other alloys. Its debut application to Section III, however, concerns nuclear safety and naturally warrants objective, impartial, and thorough technical scrutiny. In the present paper, the novel and conventional approaches are discussed. Necessary improvements to the novel approach are recommended for its application to nuclear structural component design and analysis, and for its potential expanded use to other alloys.

Ren, Weiju↗
DOE OSTI2020

XPlacer/Tracer

XPlacer/Tracer is a dynamic analysis tool that finds bad memory access patterns in heterogeneous codes. XPlacer/Tracer consists of two components. (1) A configurable ROSE plugin for source code instrumentation of heterogeneous code written in the C/C++ and CUDA programming languages. (2) A sample configuration that instruments memory accesses to dynamic memory in CPU and GPU codes, and a runtime library that tracks these memory accesses at runtime. The collected information is reported in form of a textual summary or as memory map that can be converted to images.

Pirkelbauer, PeterM.↗
DOE OSTI2022

Data and scripts associated with the manuscript "Encoding Diel Hysteresis and the Birch Effect in Dryland Soil Respiration Models through Knowledge-Guided Deep Learning"

This package contains the data and scripts used in "Encoding Diel Hysteresis and the Birch Effect in Dryland Soil Respiration Models through Knowledge-Guided Deep Learning" (Jiang et al., 2022). The data.zip file contains the flux tower and automated chamber observations used for developing the deep learning model for modeling soil respiration. The scripts.zip file contains the Jupyter notebooks and python scripts for preprocessing the data, training the deep learning models, and postprocessing the results. The src.zip contains the source code for training the deep learning model, performing mutual information analysis, and plotting functions. The trained_models.zip contains multiple folders used for hosting the trained deep-learning models and the associated soil respiration predictions. The whole process is performed using python. We include the REAMD.md to document the python package requirements.Soil respiration in dryland ecosystems is challenging to model due to its complex interactions with environmental drivers. Knowledge-guided deep learning provides a much more effective means of accurately representing these complex interactions than traditional Q10-based models. Mutual information analysis revealed that future soil temperature shares more information with soil respiration than past soil temperature, consistent with their clockwise diel hysteresis. We explicitly encoded diel hysteresis, soil drying, and soil rewetting effects on soil respiration dynamics in a newly designed Long Short Term Memory (LSTM) model. The model takes both past and future environmental drivers as inputs to predict soil respiration. The new LSTM model substantially outperformed three Q10-based models and the Community Land Model when reproducing the observed soil respiration dynamics in a semi-arid ecosystem. The new LSTM model clearly demonstrated its superiority for temporally extrapolating soil respiration dynamics, such that the resulting correlation with observational data is up to 0.7 while the correlations of both Q10-based models and the Community Land Model (CLM) are less than 0.4. Our results underscore the high potential for knowledge-guided deep learning to replace Q10-based soil respiration modules in Earth system models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Historical NTS digitizer file format

The historical NTS *.dig data formal is not widely known. I document the proper *.dig file format. I include the MATLAB code used to read *.dig files with the historical data analysis software, "eXreme Las Vegas".

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

EvaluateFlux, VARPOW, VARPEAK, and DIF3DtoVTK Utility Programs for DIF3D

The DIF3D-VARIANT solver is part of the DIF3D code which was developed at ANL for engineering level predictive analysis of nuclear reactor cores. Over the course of the last 20 years, the DIF3D-VARIANT option of DIF3D has become increasingly more used because of improvements in computer memory capabilities and performance. This is beneficial to the users of DIF3D as DIF3D-VARIANT is able to apply both p- and h- spatial mesh refinement strategies in diffusion and transport theory. Given its greater use, utility programs were created to assist in post-processing the DIF3D output. This document discusses the basic execution process of DIF3D and the output files it creates but is primarily focused on being the manual for the utility programs EvaluateFlux, VARPOW, VARPEAK, and DIF3DtoVTK.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2023

Modeling of Prismatic High Temperature Reactors in Pronghorn

Pronghorn is a Multiphysics Object-Oriented Simulation Environment (MOOSE) based thermal-hydraulics code developed at Idaho National Laboratory (INL) for advanced reactor analysis. It has been previously applied to model Pebble-Bed High Temperature Reactors (High Temperature Reactor (HTR)s), Liquid-Metal Cooled Reactors, and Molten Salt Reactors, among others. This work applies the coarse-mesh thermal hydraulics capabilities in Pronghorn to model Prismatic-Core HTRs. In particular, the Oregon State University (OSU)’s High Temperature Test Facility (HTTF) is modeled with Pronghorn. The HTTF is a 1:4 height scaled-down facility of General Atomics’ Modular High Temperature Gas-cooled Reactor.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Case Study: Leveraging GenAI to Build AI-based Surrogates and Regressors for Modeling Radio Frequency Heating in Fusion Energy Science

This work presents a detailed case study on using Generative AI (GenAI) to develop AI surrogates for simulation models in fusion energy research. The scope includes the methodology, implementation, and results of using GenAI to assist in model development and optimization, comparing these results with previous manually developed models.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Electric Vehicle Supply Equipment and Considerations for a Reasonable Rate of Return

This white paper identifies the following recommendations for states as they consider issues related to electric vehicle supply equipment program income under the National Electric Vehicle Infrastructure program and other programs covered by National Electric Vehicle Infrastructure Standards and Requirements in the U.S. Code of Federal Regulations (23 CFR 680): 1. Conduct value analysis for better outcomes 2. Promote pricing transparency

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2026

EvaluateFlux, VARPOW, VARPEAK, and DIF3DtoVTK Utility Programs for DIF3D (Rev. 1)

The DIF3D-VARIANT solver is part of the DIF3D code which was developed at ANL for engineering level predictive analysis of nuclear reactor cores. Over the course of the last 20 years, the DIF3D-VARIANT option of DIF3D has become increasingly more used because of improvements in computer memory capabilities and performance. This is beneficial to the users of DIF3D as DIF3D-VARIANT is able to apply both p- and h-spatial mesh refinement strategies in diffusion and transport theory. Given its greater use, utility programs were created to assist in post-processing the DIF3D output. This document discusses the basic execution process of DIF3D and the output files it creates but is primarily focused on being the manual for the utility programs EvaluateFlux, VARPOW, VARPEAK, and DIF3DtoVTK.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

Need for advanced research reactors for the next-generation reactor physics, analysis tools, and technology

Full text of publication follows. There is an urgent need for design and deployment of advanced research and test reactors in support of design, licensing and operation of advanced power reactors and education of next generation nuclear workforce. Existing research reactors mostly were designed and constructed decades ago with the main objectives of training operators, performing reactor physics experiments, and educating nuclear engineers and scientists. There are already gaps and significant concern about future capabilities for the existing research reactor facilities to address modern instrumentation and/or flexible environments for: performing reactor physics studies for advanced designs which have significantly different core materials forms and compositions, reactor shapes and size; validation of advanced high-fidelity software; development of machine learning algorithms for enhancement of human-machine collaboration in support of reactor monitoring, operation and safeguards; and, effective education of the next-generation workforce. The authors will focus on the need for advanced research reactors to improve and validate fast and accurate simulation tools for high-fidelity modeling and analysis of nuclear reactors in support of their design, optimization, licensing, operation, and monitoring. In the past, simulation tools were limited to relatively coarse models using approximate methodologies that benefited from two main factors: i) allowance for large margins and tolerances; ii) ability to construct prototype (e.g., zero power) reactors for adjustment of approximate methodologies. The next generation reactors have to be designed mainly by using novel high-fidelity computational tools that are accurate and fast, and therefore can be used for parametric studies and uncertainty quantification. To sufficiently demonstrate the accuracy of these tools, advanced research reactors are needed. The authors argue the need for new computational paradigms such as the MRT (Multistage, Response- function Transport) methodology which has resulted in the development of the novel high-fidelity RAPID (Real-time Analysis for Particle-transport and In-situ Detection) code system. Such code systems have to be robust in modeling any complex system, and should be fast and accurate, henceforth their uncertainties can be quantified at reasonable costs. Again, advanced research reactors are needed for the validation of the fidelity and accuracy of new computational tools. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2024

Overview of Shielding Analyses at Oak Ridge National Laboratory’s Spallation Neutron Source Second Target Station

The Neutronics Group of the Second Target Station project at Oak Ridge National Laboratory is responsible for all neutronics analyses related to design and construction. This paper provides an overview of four neutronics analyses performed for the Second Target Station project, which is representative of all the ongoing work but especially tasks related to shielding. These analyses extend from the proton accelerator through the target monolith and bunker to the end of a neutron beamline. Each example highlights the tools and methods the Neutronics Group uses for analysis. The primary tool is the Monte Carlo radiation transport code MCNP 6.2, but this is augmented by other codes that supplement the input of MCNP. The other codes specifically highlighted in this paper include Attila4MC, ADVANTG, and AARE.

Miller, Thomas↗
DOE OSTI2024

How to Build a Quantum Supercomputer: Scaling from Hundreds to Millions of Qubits

In the span of four decades, quantum computation has evolved from an intellectual curiosity to a potentially realizable technology. Today, small-scale demonstrations have become possible for quantum algorithmic primitives on hundreds of physical qubits and proof-of-principle error-correction on a single logical qubit. Nevertheless, despite significant progress and excitement, the path toward a full-stack scalable technology is largely unknown. There are significant outstanding quantum hardware, fabrication, software architecture, and algorithmic challenges that are either unresolved or overlooked. These issues could seriously undermine the arrival of utility-scale quantum computers for the foreseeable future. Here, we provide a comprehensive review of these scaling challenges. We show how the road to scaling could be paved by adopting existing semiconductor technology to build much higher-quality qubits, employing system engineering approaches, and performing distributed quantum computation within heterogeneous high-performance computing infrastructures. These opportunities for research and development could unlock certain promising applications, in particular, efficient quantum simulation/learning of quantum data generated by natural or engineered quantum systems. To estimate the true cost of such promises, we provide a detailed resource and sensitivity analysis for classically hard quantum chemistry calculations on surface-code error-corrected quantum computers given current, target, and desired hardware specifications based on superconducting qubits, accounting for a realistic distribution of errors. Furthermore, we argue that, to tackle industry-scale classical optimization and machine learning problems in a cost-effective manner, heterogeneous quantum-probabilistic computing with custom-designed accelerators should be considered as a complementary path toward scalability.

Mohseni, Masoud↗
DOE OSTI2025

Restructuring and Optimizing Reactor Building Lifting Processes & Designing a Solution for an Overhead Door Handling Forklift Attachment

This poster presents two innovative projects aimed at enhancing operational efficiency and safety at the Advanced Test Reactor (ATR) Complex. The first project focuses on restructuring the existing lift book used for hoisting operations within the ATR Reactor Building. The current lift book, a cumbersome 150+ page document, is being transformed into a more efficient format using charts that allow for quick identification of maximum lift heights based on object footprint and weight. This new method also considers various parameters such as floor integrity and reactor status, dividing entries into four distinct charts to improve usability and safety during lifts. The second project involves designing a specialized forklift attachment for handling an overhead door at the ATR Reactor Building. The attachment is engineered to securely lift and lower a 1200lb, 14ft long door, ensuring safe replacement operations. The design process included research on forklift attachment codes, modeling in Autodesk Inventor, and testing through Finite Element Analysis (FEA) and hand calculations to confirm the attachment's structural integrity. Future work includes completing detailed drawings and an Engineering Calculations Analysis and Review (ECAR) document to proceed with manufacturing and assembly. Together, these projects demonstrate a commitment to optimizing reactor building operations through innovative engineering solutions and safety considerations.

42 - ENGINEERING↗
DOE OSTI2024

The Pixel Anomaly Detection Tool : a user-friendly GUI for classifying detector frames using machine-learning approaches

Data collection at X-ray free electron lasers has particular experimental challenges, such as continuous sample delivery or the use of novel ultrafast high-dynamic-range gain-switching X-ray detectors. This can result in a multitude of data artefacts, which can be detrimental to accurately determining structure-factor amplitudes for serial crystallography or single-particle imaging experiments. Here, a new data-classification tool is reported that offers a variety of machine-learning algorithms to sort data trained either on manual data sorting by the user or by profile fitting the intensity distribution on the detector based on the experiment. This is integrated into an easy-to-use graphical user interface, specifically designed to support the detectors, file formats and software available at most X-ray free electron laser facilities. The highly modular design makes the tool easily expandable to comply with other X-ray sources and detectors, and the supervised learning approach enables even the novice user to sort data containing unwanted artefacts or perform routine data-analysis tasks such as hit finding during an experiment, without needing to write code.

47 OTHER INSTRUMENTATION↗